Business Intelligence Best Practices for Success

Business Intelligence (BI) is in a high adoption and high growth area, as users quickly value the capabilities and increasingly demand more features to compete in today's economic climate. However, from a return on investment (ROI) standpoint, BI is similar to ERP and CRM, in that it has a poor risk/reward profile, as it regularly runs into cost overruns, due to scope creep and limitless requests for support from end-users (Bernard 2009). Unlike operational systems which often have specific requirements and implementation completion timelines, BI environments are constantly evolving to meet business and information requirements (Moss 2007). Given the complexity of most system implementations, no single measure exists for Business Intelligence success. In order to effectively evaluate BI success, measures are developed to identify critical implementation factors based on the research objectives and investigation (Wixom 2001). As an organization progresses in BI maturity, the value of its activities expands. Successful organizations increasingly utilize analytical approaches to identify and enact modest improvements that increase profitability and return on business intelligence investments. This paper presents several key findings, lessons learned, success evaluation methods, and best practices as identified through prior literature review and a formal empirical study, which extends and enhances prior literature and understanding of BI.